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Improving operational efficiency begins with measuring it. Since operational efficiency is about the output to input ratio, it must be measured on both the input and output side. Quite often, company management is measuring primarily on the input side, e.g., the unit production cost or the man hours required to produce one unit.
People, process and technology is one commonly used definition, [1] process, organization and technology is another. [2] An organization is a complex system for delivering value. An operating model breaks this system into components, showing how it works. It can help different participants understand the whole.
Operations management textbooks usually cover demand forecasting, even though it is not strictly speaking an operations problem, because demand is related to some production systems variables. For example, a classic approach in dimensioning safety stocks requires calculating the standard deviation of forecast errors .
The efficiency ratio indicates the expenses as a percentage of revenue (expenses / revenue), with a few variations – it is essentially how much a corporation or individual spends to make a dollar; entities are supposed to attempt minimizing efficiency ratios (reducing expenses and increasing earnings). The concept typically applies to banks.
A single integrated management system may reduce overlap, redundancy, and conflict. Early adopters of this practice include companies such as ExxonMobil and Chevron , which have implemented the Operations Integrity Management System (OIMS) [ 7 ] and the Operations Excellence Management System (OEMS), [ 8 ] respectively.
In particular, Ethernet operations, administration and maintenance (EOAM) is the protocol for installing, monitoring and troubleshooting Ethernet metropolitan area network (MANs) and Ethernet WANs. The OAM features covered by this protocol are discovery, link monitoring, remote fault detection and remote loopback .
In statistics, efficiency is a measure of quality of an estimator, of an experimental design, [1] or of a hypothesis testing procedure. [2] Essentially, a more efficient estimator needs fewer input data or observations than a less efficient one to achieve the Cramér–Rao bound.
Data envelopment analysis (DEA) is a nonparametric method in operations research and economics for the estimation of production frontiers. [1] DEA has been applied in a large range of fields including international banking, economic sustainability, police department operations, and logistical applications [2] [3] [4] Additionally, DEA has been used to assess the performance of natural language ...